• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.957-960
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• 1995

A new method is introduced for the parametrization in B-spline surface interpolation. THis method uses the basis function to assign the parameter values to the arbitrary set of geometric data. This method gives us several important advantages in geometric modeling.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.640-642
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• 1998

When resampling an image to a new set of coordinates, there is often a noticeable loss in image quality. The interpolation kernel determines the quality of interpolation. In this paper, We think two interpolation methods: cubic-spline method, neural net method, at first study given interpolation method using spline and then present new interpolation methon using SOFM and LAM(neural net method), finally compare the performance of several interpolation methods including replication, bilinear, spline and new methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.474-479
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• 2003

This paper addresses the problem of B-spline surface interpolation to serial contours, where the number of points varies from contour to contour. A traditional lofting approach creates a set of B-spline curves via B-spline curve interpolation to each contour, makes them compatible via degree elevation and knot insertion, and performs B-spline surface lofting to get a B-spline surface interpolating them. The approach tends to result in an astonishing number of control points in the resulting B-spline surface. This situation arises mainly from the inevitable process of progressively merging different knot vectors to make the B-spline curves compatible. This paper presents a new approach for avoiding this troublesome situation. The approach includes a novel process of getting a set of compatible B-spline curves from the given contours. The process is based on the universal parameterization [1,2] allowing the knots to be selected freely but leading to a more stable linear system for B-spline curve interpolation. Since the number of control points in each compatible B-spline curve is equal to the highest number of contour points, the proposed approach can realize efficient data reduction and provide a compact representation of a B-spline surface while keeping the desired surface shape. Some experimental results demonstrate its usefulness and quality.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.381-386
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• 2001

When a input image is extensively magnified on the computer system, it is almost impossible to replicate the original shape because of mismatched coordinates system. In order to resolve the problem, the shape of the magnified image has been reconfigured using the bilinear interpolation method, low pass special filtering interpolation method and B-spline interpolation method, Ferguson curve interpolation method based on the CAD/CAM curve interpolation algorithm. The computer simulation main result was that. Nearest neighbor interpolation method is simple in making the interpolation program but it is not capable to distinguish the original shape. Bilinear interpolation method has the merit to make the magnified shape smooth and soft but calculation time is longer than the other method. Low pass spatial filtering method and B-spline interpolation method has an effect to immerge the intense of the magnified shape but it is also difficult to distinguish the original shape. Ferguson curve interpolation method has sharping shape than B-spline interpolation method.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1188-1200
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• 2015

A unified numerical method for computing the quadrature weights, integration matrix, and differentiation matrix is newly developed in this study. For this purpose, a spline-like interpolation using piecewise continuous polynomials is converted into a global spline interpolation formula, with which the quadrature formulas can be derived from integration and differentiation of the transformed function in an exact manner. To prove the usefulness of the suggested approach, both the Lagrange and tension spline interpolations are represented in exactly the same form as global spline interpolation. The applicability of the proposed method on arbitrary nodes is illustrated using two different sets of nodes. A series of validations using three test functions is conducted to show the flexibility in selecting computational nodes with the present method.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.192-198
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• 2001

We consider an interpolation problem with nonuniform rational B-spline curves given ordered data points. The existing approaches assume that weight for each point is available. But, it is not the case in practical applications. Schneider suggested a method which interpolates data points by automatically determining the weight of each control point. However, a drawback of Schneiders approach is that there is no guarantee of avoiding undesired poles; avoiding negative weights. Based on a quadratic programming technique, we use the weights of the control points for interpolating additional data. The weights are restricted to appropriate intervals; this guarantees the regularity of the interpolating curve. In a addition, a knot placement is proposed for pleasing interpolation. In comparison with integral B-spline interpolation, the proposed scheme leads to B-spline curves with fewer control points.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.266-270
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• 2004

The image interpolation is one of an image preprocessing process to heighten a resolution. The conventional image interpolation used much to concept that it put in other pixel to select the nearest value in a pixel simply, and use much the temporal object interpolation techniques to do the image interpolation by detecting motion in a moving picture presently. In this paper, it is proposed the image interpolation techniques using the fuzzy wavelet base function. This is applied to embody a correct edge image and a natural image when expand part of the still image by applying the fuzzy wavelet base function coefficient to the conventional B-spline function. And the proposal algorithm in this paper is confirmed to improve about 1.2831 than the image applying the conventional B-spline function through the computer simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.358-363
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• 1998

An algorithm for representing the cubic spline interpolation of differentiable functions by a fuzzy system is presented in this paper. The cubic B-spline functions which form a basis for the interpolation function are used as the fuzzy sets for input fuzzification. The ordinal number of the coefficient cKL in the list of the coefficient cij's as sorted in increasing order, is taken to be the output fuzzy set number in the (k, l) th entry of the fuzzy rule table. Spike functions are used for the output fuzzy sets, with cij's as support boundaries after they are sorted. An algorithm to compute the support boundaries explicitly without solving the matrix equation involved is included, along with a few properties of the fuzzy rule matrix for the designed fuzzy system.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.126-131
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• 1999

Up until now, it is said that no satisfactory computer solutions have been found for synthesizing four-bar linkage based on the prescribed coupler link curve. In our study, an algorithm has been developed to improve the design synthesis of four-bar linkage automatically generating prescribed path by using B-spline interpolation. The suggested algorithm generates the desired coupler curve by using B-spline interpolation, and hence the generated curve approximates as closely as to the desired curve representing coupler link trajectory. Also, when comparing each generated polygon with the control polygon, rapid comparison by applying convex hull concept. finally, optimization process using ADS is incorporated into the algorithm based on the 5 precision point method to reduce the total optimization process time. As for examples, three different four-bar linkages were tested and the results showed the effectiveness of the algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.683-688
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• 2009

The purposes of this paper is to propose new techniques to reconstruct measured optical images by using the template matching and B-Spline interpolation method based on image processing technology. To do this, we detect the matching template and non-matching template from each optical image. And then, we match the overlaped images from base level by correcting roll, pitch, and yaw error of images. At last, the matching image is interpolated by B-Spline interpolation. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.